License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.NG-RES.2022.3
URN: urn:nbn:de:0030-drops-161118
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2022/16111/
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Leva, Alberto ; Formentin, Simone ; Seva, Silvano

Overlapping-Horizon MPC: A Novel Approach to Computational Constraints in Real-Time Predictive Control

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OASIcs-NG-RES-2022-3.pdf (0.8 MB)

Abstract

Model predictive control (MPC) represents the state of the art technology for multivariable systems subject to hard signal constraints. Nonetheless, in many real-time applications MPC cannot be employed as the minimum acceptable sampling frequency is not compatible with the computational limits of the available hardware, i.e., the optimisation task cannot be accomplished in one sampling period. In this paper we generalise the classical receding-horizon MPC rationale to the case where n > 1 sampling intervals are required to compute the control trajectory. We call our scheme Overlapping-horizon MPC - OH-MPC for short - and we numerically show its attitude at providing a tunable trade-off between optimisation quality and real-time capabilities.

BibTeX - Entry

@InProceedings{leva_et_al:OASIcs.NG-RES.2022.3,
  author =	{Leva, Alberto and Formentin, Simone and Seva, Silvano},
  title =	{{Overlapping-Horizon MPC: A Novel Approach to Computational Constraints in Real-Time Predictive Control}},
  booktitle =	{Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022)},
  pages =	{3:1--3:10},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-221-1},
  ISSN =	{2190-6807},
  year =	{2022},
  volume =	{98},
  editor =	{Bertogna, Marko and Terraneo, Federico and Reghenzani, Federico},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2022/16111},
  URN =		{urn:nbn:de:0030-drops-161118},
  doi =		{10.4230/OASIcs.NG-RES.2022.3},
  annote =	{Keywords: real-time control, model predictive control}
}

Keywords: real-time control, model predictive control
Collection: Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022)
Issue Date: 2022
Date of publication: 11.06.2022

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